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Queensland local communities to benefit from data analytics

News Release

Wednesday, 17 October 2017

Initial trials identified as much as $5 million in potential savings

The prospect of finding new solutions to community problems like barking dogs and the need to be as efficient as possible in using energy and managing vehicle fleets has driven local councils to embrace a new data analytics tool launched by the Local Government Association of Queensland.

The tool, dubbed LG Sherlock, promises to help local councils analyse the huge amounts of data they hold to find innovative ways to save money and become more efficient in serving their communities.

LG Sherlock, launched at the LGAQ annual conference in Gladstone today, relies on the information created by smart technologies associated with meters, lights, pumps, switches, vehicle tracking and wifi to produce insights that could help resolve issues affecting local communities.

LGAQ President Sunshine Coast Mayor Mark Jamieson said early trials of LG Sherlock had identified as much as $5 million in potential savings for councils.

He said LG Sherlock was a tool that councils needed to put their data to work, to connect it to other data, and to convert the combined and collated information back into 'practical, useful insights' into the way they did business.

'This information is too valuable to leave sitting on the shelf – untapped and under-utilised,' he said.

'LG Sherlock aims to make sense of all this data. It will centralise the data, get it working together and get it producing insights.'

Councils could use the new tool to help with challenges like animal management and, in particular, barking dogs, one of the most common issues for councils across Queensland.

LG Sherlock has the capacity to tell councils not only which dog breeds bark the most, but in what places, at what times, under what weather conditions.

Such information could be fed back into council animal management plans and their communications with dog owners and breeders.

LG Sherlock was developed for the LGAQ by data analytics experts at consultants Accenture and Amazon Web Services.